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✔本篇論文使用華聯產品：Human OneArray

J Infect Dis. 2010, 202(2):282-90. doi: 10.1086/653484.

Transcriptional profiling of Clostridium difficile and Caco-2 cells during infection

Janvilisri T, Scaria J, Chang Yf.

AbstractClostridium difficile is well recognized as the most common infectious cause of nosocomial diarrhea. The incidence and severity of C. difficile infection (CDI) is increasing worldwide. Here, we evaluated simultaneously the transcriptional changes in the human colorectal epithelial Caco-2 cells and in C. difficile after infection. A total of 271 transcripts in Caco-2 cells and 207 transcripts in C. difficile were significantly differentially expressed at 1 time point during CDI. We used the gene ontology annotations and protein-protein network interactions to underline a framework of target molecules that could potentially play a key role during CDI. These genes included those associated with cellular metabolism, transcription, transport, cell communication, and signal transduction. Our data identified certain key factors that have previously been reported to be involved in CDI, as well as novel determinants that may participate in a complex mechanism underlying the host response to infection, bacterial adaptation, and pathogenesis.

AbstractBackground
Tuberculosis (TB) is a serious infectious disease in that 90 % of those latently infected with Mycobacterium tuberculosis present no symptoms, but possess a 10 % lifetime chance of developing active TB. To prevent the spread of the disease, early diagnosis is crucial. However, current methods of detection require improvement in sensitivity, efficiency or specificity. In the present study, we conducted a microarray experiment, comparing the gene expression profiles in the peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population.
Results
Bioinformatics analysis revealed that most of the differentially expressed genes belonged to immune responses, inflammation pathways, and cell cycle control. Subsequent RT-PCR validation identified four differentially expressed genes, NEMF, ASUN, DHX29, and PTPRC, as potential biomarkers for the detection of active and latent TB infections. Receiver operating characteristic analysis showed that the expression level of PTPRC may discriminate active TB patients from healthy individuals, while ASUN could differentiate between the latent state of TB infection and healthy condidtion. In contrast, DHX29 may be used to identify latently infected individuals among active TB patients or healthy individuals. To test the concept of using these biomarkers as diagnostic support, we constructed classification models using these candidate biomarkers and found the Naïve Bayes-based model built with ASUN, DHX29, and PTPRC to yield the best performance.
Conclusions
Our study demonstrated that gene expression profiles in the blood can be used to identify not only active TB patients, but also to differentiate latently infected patients from their healthy counterparts. Validation of the constructed computational model in a larger sample size would confirm the reliability of the biomarkers and facilitate the development of a cost-effective and sensitive molecular diagnostic platform for TB.

AbstractTuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic¡Xthe so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. In attempt to further understand the molecular pathogenesis of TB and develop efficient diagnostic biomarkers, several molecular studies have attempted to compare the gene and microRNA expression profiles between healthy controls versus active TB or LTBI patients. However, the results vary due to diverse genetic background, study designs, and the inherent complexity of the disease process. Thus, developing a sensitive and efficient method for the detection of LTBI is both crucial and challenging. For the present study, we performed a systematic analysis of the gene and microRNA profiles of healthy individuals versus those affected with TB or LTBI. Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs, presenting to be useful molecular signatures to help enhance the understanding of TB pathogenesis. Furthermore, some of these molecular interactions are novel, and may serve as potential biomarkers of TB and LTBI, facilitating the development for a more sensitive, efficient, and cost-effective diagnostic assay for TB and LTBI for the Taiwanese population.

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✔本篇論文使用華聯產品：Human OneArray

Bmc Cancer. DOI 10.1186/s12885-015-1671-5.

Upregulation of MicroRNA-19b predicts good prognosis in patients with hepatocellular carcinoma presenting with vascular invasion or multifocal disease

AbstractBackground
After surgical resection of hepatocellular carcinoma (HCC), recurrence is common, especially in patients presenting with vascular invasion or multifocal disease after curative surgery. Consequently, we examined the expression pattern and prognostic value of miR-19b in samples from these patients.
Methods
We performed a miRNA microarray to detect differential expression of microRNAs (miRNAs) in 5 paired samples of HCC and non-tumoral adjacent liver tissue and a quantitative real-time polymerase chain reaction (PCR) analysis to validate the results in 81 paired samples of HCC and adjacent non-tumoral liver tissues. We examined the associations of miR-19b expression with clinicopathological parameters and survival. MiR-19b was knocked down in Hep3B and an mRNA microarray was performed to detect the affected genes.
Results
In both the miRNA microarray and real-time PCR, miR-19b was significantly overexpressed in the HCC tumor compared with adjacent non-tumor liver tissues (P